MétaCan
Menu
← Back to cohort
Record W4385331113 · doi:10.2196/42964

Efficient Generation of Chondrocytes From Bone Marrow–Derived Mesenchymal Stem Cells in a 3D Culture System: Protocol for a Practical Model for Assessing Anti-Inflammatory Therapies

2023· article· en· W4385331113 on OpenAlexvenueno aff
Rajashree Patnaik, Shirin Jannati, Bala Mohan Sivani, Manfredi Rizzo, Nerissa Naidoo, Yajnavalka Banerjee

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersMohammed Bin Rashid University of Medicine and Health Sciences
KeywordsMesenchymal stem cellCartilageChondrocyteCell biologyBone marrowStem cellProinflammatory cytokineInflammationChemistryMedicineImmunologyBiologyAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND: Chondrocytes are the primary cells responsible for maintaining cartilage integrity and function. Their role in cartilage homeostasis and response to inflammation is crucial for understanding the progression and potential therapeutic interventions for various cartilage-related disorders. Developing an accessible and cost-effective model to generate viable chondrocytes and to assess their response to different bioactive compounds can significantly advance our knowledge of cartilage biology and contribute to the discovery of novel therapeutic approaches. OBJECTIVE: We developed a novel, streamlined protocol for generating chondrocytes from bone marrow-derived mesenchymal stem cells (BMSCs) in a 3D culture system that offers significant implications for the study of cartilage biology and the discovery of potential therapeutic interventions for cartilage-related and associated disorders. METHODS: We developed a streamlined protocol for generating chondrocytes from BMSCs in a 3D culture system using an "in-tube" culture approach. This simple pellet-based 3D culture system allows for cell aggregation and spheroid formation, facilitating cell-cell and cell-extracellular matrix interactions that better mimic the in vivo cellular environment compared with 2D monolayer cultures. A proinflammatory chondrocyte model was created by treating the chondrocytes with lipopolysaccharide and was subsequently used to evaluate the anti-inflammatory effects of vitamin D, curcumin, and resveratrol. RESULTS: The established protocol successfully generated a large quantity of viable chondrocytes, characterized by alcian blue and toluidine blue staining, and demonstrated versatility in assessing the anti-inflammatory effects of various bioactive compounds. The chondrocytes exhibited reduced inflammation, as evidenced by the decreased tumor necrosis factor-α levels, in response to vitamin D, curcumin, and resveratrol treatment. CONCLUSIONS: Our novel protocol offers an accessible and cost-effective approach for generating chondrocytes from BMSCs and for evaluating potential therapeutic leads in the context of inflammatory chondrocyte-related diseases. Although our approach has several advantages, further investigation is required to address its limitations, such as the potential differences between chondrocytes generated using our protocol and those derived from other established methods, and to refine the model for broader applicability and clinical translation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.258
GPT teacher head0.502
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research Protocols→Same topicOsteoarthritis Treatment and Mechanisms→French-language works237,207→